In requests for information, discovery proceedings, general research, etc., a large body of information must be examined to find and extract relevant documents. When a non-sorted, and even disparate, collection of documents is examined, the relevant documents can be a very small fraction of the overall body of information. Furthermore, in many cases, the documents needed may not be readily apparent from titles, keywords, or other direct identifying means. When the body of information becomes large enough, it becomes untenable for a human to perform a search and analysis of each individual document due to either time, expense, or both. Furthermore, humans may apply different standards to their searching, resulting in inconsistent results. As a result, automated processes of document examination and retrieval, while are typically limited by the intelligence of the searching algorithm, are being increasingly adopted.